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Seventeen things to ask when scoping. By Jody Padar Radical Pricing – By The Radical CPA Go PRO for members-only access to more Jody Padar. View the full article

Seventeen things to ask when scoping. By Jody Padar Radical Pricing – By The Radical CPA Go PRO for members-only access to more Jody Padar. View the full article

Internal controls are no good on their own. By Ed Mendlowitz 77 Ways to Wow! Go PRO for members-only access to more Edward Mendlowitz. View the full article

Internal controls are no good on their own. By Ed Mendlowitz 77 Ways to Wow! Go PRO for members-only access to more Edward Mendlowitz. View the full article

What are your clients saying about you? By August Aquila MAX: Maximize Productivity, Profitability and Client Retention Go PRO for members-only access to more August J. Aquila. View the full article

What are your clients saying about you? By August Aquila MAX: Maximize Productivity, Profitability and Client Retention Go PRO for members-only access to more August J. Aquila. View the full article

OpenAI unleashed Sora 2 last month, the final boss of slop machines (at least for now). The social app draws entirely from artificial intelligence: Instead of sharing photos and videos of themselves, users can opt in for “cameos” and create fake clips that depict themselves or their friends in any scenario imaginable. It’s mostly being used to make viral meme content and the type of short-form videos you’d scroll past on TikTok, albeit with deepfakes. Sora doesn’t allow you to make videos of other living people (dead celebrities and SpongeBob SquarePants characters are fair game) unless given express permission. As one user put it: “Digital Taxidermy is the craziest yet most accurate description of the AI slop videos of people who’ve passed away.” “OpenAI in 2021: “we want to cure brain cancer,” another X post read, responding to the announcement. “OpenAI in 2025: “we’re becoming brain cancer.” Upon the app’s release, one of the first breakout stars was none other than CEO Sam Altman. “You either die a hero or build Sora 2 and become meme material,” an X post read with an AI generated Altman posing as a K-Pop star, wearing a crop top and dark nail varnish. Another X user used Sora to make an AI video of Altman wearing baggy clothes and outfit and thick gold chains, rapping about his company’s success. “Sam Altman dressed like a 2000s rapper is rapping about how Sora is bankrupting all other AI video companies, ending every line with ‘what happened to that boy, brrr,” they posted. Responding to the influx of memes, Altman wrote on X, “it is way less strange to watch a feed full of memes of yourself than I thought it would be. Not sure what to make of this.” In another popular Sora 2 deepfake, Altman is busted stealing GPUs from Target. Luiza Jarovsky wrote: “It is AS IF they are encouraging people to create fake videos of people committing crimes, being humiliated, or in all sorts of embarrassing situations.” She added. “The AI-powered ‘deepfakezation’ of the internet is here and it will not be beautiful.” Just days after launch, journalist Taylor Lorenz also announced that a “psychotic stalker” was already using Sora 2 to make deepfake videos of her. “It is scary to think what AI is doing to feed my stalker’s delusions,” Lorenz wrote. Others however, are embracing the slop life. “Bob Ross vibe coding was the AI slop I never knew I needed in my life,” one post read. Another big meme on Sora is making it appear as if Jake Paul is coming out the closet or give makeup tutorials. Paul himself appears to be in on the joke. “I’ve had it with the AI stuff,” he said in a Wednesday video. “It’s affecting my relationships, businesses. It’s really affecting things, and people really need to get a life,” he added, all the while dabbing foundation on his face. View the full article

Amazon unexpectedly pulled out of Google Shopping auctions in late July, shaking up paid search. Retailers quickly filled the gap, driving stronger click growth and easing ad costs across Google and Microsoft. That’s according to marketing agency Tinuiti, which today released its Digital Ads Benchmark Report Q3 2025. Here are some of the key takeaways from Tinuiti’s report. Google Search – more clicks, lower prices. Ad spend rose 10% year over year, as clicks jumped 11% – the fifth straight quarter of acceleration. CPCs fell 1%, reversing a 3% rise from Q2. Shopping ads surged: clicks up 15%, CPCs down 1%, spend up 14%. Temu and Shein returned to Google Shopping in mid-2025, offsetting Amazon’s exit, while Walmart captured more visibility. Performance Max gains momentum. Google’s Performance Max (PMax) campaigns continued to advance, accounting for 68% of shopping ad spend in Q3, up from 59% in Q2. PMax generated 2% higher conversion rates and 5% higher sales per click than standard Shopping campaigns, though its ROAS was 2% lower due to higher CPCs. Non-shopping placements made up 33% of PMax spending, with YouTube video impressions doubling from 5% to 9%. Text ads regain traction. Google text ads saw 8% year-over-year spend growth and a return to positive click volume after several slow quarters. Brand CPCs cooled from 19% growth in Q1 to 5% in Q3, while non-brand CPCs fell 7%. Advertisers are experimenting with new AI Max campaigns, though they remain a small share of activity. Microsoft steady, but slower. Microsoft search ad spending rose 12% year over year with click growth just under 15% and CPCs down 2%. Amazon remained active in Microsoft Shopping ads even as it paused its Google program. Why we care. Amazon’s withdrawal left a vacuum that improved performance for other retailers and gave Google room to stabilize pricing and auction dynamics. The shift also highlights how quickly competitive dynamics can change in digital advertising. At the same time, Google’s Performance Max growth signals that automation and AI-driven campaign management are becoming central to maintaining efficiency and reach in a more fluid, platform-driven marketplace. Bottom line. Google’s paid search ecosystem adjusted to Amazon’s absence, delivering higher volumes at lower prices, based on Tinuiti’s Q3 data. Meanwhile, Performance Max continued to reshape the landscape as automation and AI optimization gained traction with advertisers. Tinuiti’s report. Digital Ads Benchmark Report Q3 2025 (registration required) View the full article

Content chunking is breaking down content into smaller “chunks“ that are easier for AI systems to process. View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. If you're like most people, your TV is the centerpiece of your living room decor. That means when it's off, all your furniture is pointed at a black rectangle. If this bothers you, the "art TV" trend that started with Samsung's The Frame could be the answer. These sets are made to look like a piece of art, and display an image of your choosing when not in use. The Frame is a pricey option, but other brands have their own offerings—including Hisense, and its CanvasTV. Already a more affordable alternative to The Frame, you can currently get a 55-inch Hisense CanvasTV for $694.99 (down from $999.99). This is $5 off its lowest price ever, according to price tracking tools. (Other sizes are also available at a discount.) 144Hz, Art Mode, Anti-Glare Panel, Hi-Matte Display, Frame & UltraSlim Wall Mount Included Hisense 55-Inch Class QLED $694.99 at Amazon $999.99 Save $305.00 Get Deal Get Deal $694.99 at Amazon $999.99 Save $305.00 144Hz, Art Mode, Anti-Glare Panel, Hi-Matte Display, Frame & UltraSlim Wall Mount Included Hisense 65-Inch Class QLED $997.99 at Amazon $1,299.99 Save $302.00 Get Deal Get Deal $997.99 at Amazon $1,299.99 Save $302.00 144Hz, Art Mode, Anti-Glare Panel, Hi-Matte Display, UltraSlim Wall Mount & Frame Included Hisense 75-Inch Class QLED $1,497.99 at Amazon $1,797.99 Save $300.00 Get Deal Get Deal $1,497.99 at Amazon $1,797.99 Save $300.00 144Hz, Art Mode, Anti-Glare Panel, Hi-Matte Display, UltraSlim Wall Mount & Frame Included Hisense 85-Inch Class QLED $1,997.99 at Amazon $2,097.99 Save $100.00 Get Deal Get Deal $1,997.99 at Amazon $2,097.99 Save $100.00 SEE 1 MORE The primary attraction of the CanvasTV over Samsung's The Frame is the price: You'll pay $200 to $1,000 less for the same-sized TV (depending on which size you choose). Not to mention, if you choose The Frame, you have to buy the actual frames that go around the set, and pay for most artwork separately, while Hisense includes all of that in the selling price. Like The Frame, the CanvasTV also comes with a flush TV mount that will allow you to hang it so it looks like an actual art piece. I also like that CanvasTVs come with the Google OS, which is my favorite smart TV operating system, as it lets you cast seamlessly from your phone (Android or iPhone). The CanvasTV is a QLED TV with Quantum Dot technology and 4K resolution with a 144Hz refresh rate in Game Mode Pro, according to CNET's review. What gives it the art look is the low reflection Hi-Matte display, which combats glare. You can swap out the teak frames with different colors, including white and walnut frames. Considering Hisense's take on The Frame is cheaper and includes less upfront costs, it's a great option for anyone looking to save money on a TV that won't dominate their decor—especially at the current discount. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods Pro 2 Noise Cancelling Wireless Earbuds — $197.00 (List Price $249.00) Samsung Galaxy S25 Edge 256GB Unlocked AI Phone (Titanium JetBlack) — $819.99 (List Price $1,099.99) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $319.00 (List Price $349.00) Blink Mini 2 1080p Indoor Security Camera (2-Pack, White) — $34.99 (List Price $69.99) Ring Battery Doorbell Plus — $149.99 (List Price $149.99) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $34.99 (List Price $69.99) Ring Indoor Cam (2nd Gen, 2-pack, White) — $79.99 (List Price $99.98) Amazon Fire TV Stick 4K (2nd Gen, 2023) — $29.99 (List Price $49.99) Shark AV2501S AI Ultra Robot Vacuum with HEPA Self-Empty Base — $359.89 (List Price $549.99) Amazon Fire HD 10 (2023) — (List Price $139.99) Deals are selected by our commerce team View the full article

On Reddit, Google’s John Mueller reviewed a two-day “vibe-coded” Bento Grid Generator and listed fixes for crawlability, meta tags, hreflang, and structured data. The post Google’s John Mueller Flags SEO Issues In Vibe Coded Website appeared first on Search Engine Journal. View the full article

Websites have been the foundation of SEO strategy for 20-odd years. That’s changing with AI search. When someone asks ChatGPT for a product in your category, it doesn’t always crawl websites in real-time. Its first move is to pull from what it already knows about you and your competitors from its existing knowledge. Clear and recognizable entities in AI training data are just as important as having the most authoritative and optimized website. This shift means your webpage might rank #1 in classic search, but if your brand isn’t well-structured for entities, AI might overlook you entirely in the answer. The rules we’ve relied on for decades don’t fully apply when machines create answers. They draw on their own knowledge and real-time data from sites, including yours. You’re about to learn what this means, why it matters, and what you can do about it. What Are Entities in AI Search? An entity is a “thing” that search engines and AI models can recognize, understand, and connect to other things. Think of entities as the building blocks that AI uses to construct answers. In other words, gigantic relational databases. Let’s use email marketing company Omnisend as an example. Through the lens of a database, Omnisend isn’t just a website with pages about email marketing. It’s a network of connected entities: The brand itself: Omnisend Products: Omnisend Email & SMS Marketing Platform People: Rytis Lauris (co-founder) Features: automation workflows, Shopify integration, SMS campaigns Use cases: “welcome series,” “abandoned cart recovery” Here’s what the entities look (hypothetically ) like to a large language model (LLM): These records become the foundation for AI answers. LLMs do more than just find keywords on your page. They also retrieve entities, place them in vector space, and choose the ones that best answer your question. Vector space explained: It’s a mathematical method that AI models use to understand relationships between concepts. Imagine a 3D map where similar items group together. For example, “Apple,” the company, is close to “iPhone” and “Tim Cook.” Meanwhile, “apple,” the fruit, is near “banana” and “orchard.” For example, ask Google: “What’s the best email marketing tool for my Shopify store?” You’ll see brand entities like Klaviyo, Omnisend, Brevo, Mailchimp, Privy, and MailerLite mentioned. This makes sense because the entities are closely related in the AI’s understanding. Notice: the brand mentions aren’t linked to the websites. It’s just building the answer and then linking to the brand SERP on Google. Why Entities Matter More Than Websites AI models are constantly mapping relationships between entities when serving up answers. When someone types “best email marketing tool for Shopify,” LLMs spread out the query. They turn that one question into multiple related searches. Think of AI doing lots of Google searches at the same time. The system simultaneously explores “What integrates with Shopify?”, “Which tools handle abandoned carts?” and “What do ecommerce stores actually use?” Your brand can appear through any of these paths, even if you didn’t optimize for the original query. Classic SEO relied a lot on keyword density and page authority. But AI uses dense retrieval, where it’s looking for semantic meaning across the web, not just word matches on your page. Dense retrieval explained: AI systems focus on meaning, not just exact keywords. They find related content, even if different words are used. A Reddit comment that clearly explains “We switched from Klaviyo to Omnisend because the Shopify integration actually works” carries more signal (assuming the model prioritizes authentic discussions) than a page stuffed with “best email marketing Shopify” keywords. The AI understands the relationship between the entities (Klaviyo, Omnisend, Shopify) and the context (switching, integration quality). PR folks have been fighting for this moment: mentions without links still count. For the longest time, we’ve obsessed over backlinks as the currency of SEO. But AI systems recognize when brands get mentioned alongside relevant topics, using these as relationship signals. So when Patagonia appears in climate articles without a hyperlink, when Notion shows up in productivity discussions on Reddit, when your brand gets name-dropped in a podcast transcript — these all strengthen your entity in AI’s understanding. Here’s a real example that clarified this for me: Microsoft OneNote often shows up high in AI recommendations for “note-taking tools.” In ChatGPT: In Perplexity: And in Google AI Overviews: But EverNote dominates Google’s number one ranking spot for “note taking tools”. Why? OneNote’s integration with the Microsoft ecosystem means it gets mentioned constantly in productivity discussions, enterprise software comparisons, and Office tutorials. This creates dense entity relationships in AI training data. Evernote, by contrast, has focused on SEO and earned strong backlinks that dominate traditional search rankings. How Entities Get Recognized So how does Google (and other AI systems) actually know that Omnisend is an email marketing platform and not, say, a meditation app? The answer sits at the intersection of structured data, human conversation, and pattern recognition…at massive scale. Entity Databases and Product Catalogs Google maintains what they call Knowledge Graphs and Shopping Graphs. Other AI systems have similar entity databases, just with different names. The idea is the same: huge databases that map every product, company, and person along with their attributes and relationships. When Nike releases the Pegasus 41, it doesn’t just become a new product page on Nike.com. It becomes an entity in Google’s Shopping Graph, connected to “running shoes,” “Nike,” “marathon training,” and hundreds of other nodes. The system knows it’s a shoe before anyone optimizes a single keyword. Human Conversation as Training Data AI systems learn just as much from informal mentions as they do from structured markup. When an Outdoor Gear Lab review casually mentions testing Patagonia’s Torrentshell 3L against the expensive Arc’teryx Beta SL, that relationship gets encoded. When a podcast guest says, “I moved from Asana to Notion for task and project management,” this competitive link adds to the training data. Reddit and Quora have become unexpectedly powerful for entity recognition. (Google explicitly stated they’re prioritizing “authentic discussion forums” in their ranking systems.) A single comment on why someone picked Obsidian over Notion for knowledge management matters more than you might realize. These platforms capture what websites struggle to do: real people sharing real decisions with real context. Multimodal Recognition AI systems extract entities from audio and video. They do this by turning speech into text through transcription. Every mention in a transcript, every product on screen, and every comparison in a talking-head segment is processed. A 10-minute YouTube review of project management tools turns into structured data that compares ClickUp, Notion, and Asana. It includes feature comparisons and maps out use cases. The New SEO Power Dynamic You can’t game entity recognition the way you could game PageRank. You can’t manufacture authentic Reddit discussions. You can’t fake your way into natural podcast mentions. The system rewards genuine presence in genuine conversations, not optimized anchor text. Think about what this means: Your engineering team’s conference talk that mentions your product’s architecture? That’s entity building. Your customer’s YouTube walkthrough of their workflow? Entity building. That heated Hacker News thread where someone defends your approach to data privacy? Entity building. We’ve spent the longest time optimizing for robots. Now the robots are optimized to recognize authentic human discussion. (Ironic.) 5 Ways to Optimize Your Brand for Entities (Not Just a Website) Using Omnisend as an example, here are five approaches for evaluating and optimizing entity presence in AI-powered search results. 1. Assess Your Entity Foundation To start, you need a baseline understanding of your current entity relationships. For Omnisend, this means mapping how AI systems currently categorize them relative to competitors. Begin by verifying schema markup across key pages. Testing Omnisend’s homepage with the Schema Markup Validator shows they use Organization and VideoObject schema. And the Organization schema is relatively basic. Omnisends competitor, Klaviyo, uses Organization schema as a container for multiple software offerings. Klaviyo’s approach maintains brand-level authority while declaring specific software categories and capabilities. This potentially gives them stronger entity associations for queries about email marketing, SMS marketing, and marketing automation. Next, check your entity presence in major knowledge sources like Wikidata and Crunchbase. On Wikidata, Omnisend’s records are OKAY. There’s basic info, like what Omnisend does, the industry, inception date, URL, and social media profiles. But Klaviyo, again, is all over it. They have multiple properties for industry, entity type, URLs, offerings, and even partnerships. There’s a clear opportunity for Omnisend to update its Wikidata with more details. 2. Test Query Decomposition AI systems break down queries into entities and relationships. Then, they may try multiple retrievals. For example, in Google Chrome, I prompted ChatGPT: “What’s the best email marketing tool for ecommerce in 2025? My priority is deliverability.” In the chat URL, copy the alphanumeric sequence after the /c/ directory. For me, it was 68d4e99e-4818-8332-adbd-efab286f4007. Note: You need to be logged into ChatGPT to get this sequence Right-click on the page and click “Inspect”. Choose the “Network” tab, paste the alphanumeric sequence in the filter field, and reload the page. In the “Find” section, search for “search_model_queries“. Then, click on the search results. The first decomposed queries are: “2025 email deliverability test ecommerce ESP Klaviyo Omnisend Drip 2024 2025” “EmailToolTester deliverability test 2024 results Klaviyo Omnisend” “Klaviyo deliverability benchmark 2024 ecommerce” And the second set is: “Validity crisis of deliverability 2025 benchmark report inbox placement” “Benchmark inbox placement 2025 ESP comparison seed tests” Each decomposed query represents a different competitive pathway. Omnisend might surface through deliverability discussions, but miss general tool comparisons. Mailchimp could dominate broad searches while competitors own specialized angles. This explains why you appear in AI answers for searches you never optimized for. The semantic understanding creates visibility through unexpected entity relationships rather than keyword matching. You can check this yourself. Run the extracted queries in separate chats and note which brands appear where. But maybe don’t build a strategy around exploiting this technique. The methodology depends on undocumented functionality that OpenAI could change without notice. Important finding: Simple queries produce simple results. When I prompted “Best email marketing tool for ecommerce,” it triggered exactly one internal search with basically the same language. No decomposition. 3. Map Competitive Entity Relationships Traditional SEO competitive analysis asks “Who ranks for our keywords?” Entity analysis asks “When do AI systems group us together?” I tested this with Omnisend to understand when they appear alongside different competitors. I ran 15 variations of email marketing queries through Google AI Mode to see which brands consistently appear together. Note: I tested logged out, using a VPN set to San Francisco, in private browsing mode to minimize personalization bias. I began with simple terms like “best email marketing for ecommerce” and “abandoned cart recovery tools.” Then, I tried different angles like “email automation for Shopify stores.” Here’s what I found: Query Context Omnisend Present Most Co-Mentioned Klaviyo Present Ecommerce email 5/5 queries Klaviyo, Mailchimp 4/5 queries General email 5/5 queries Mailchimp, Brevo 2/5 queries Deliverability focus 2/5 queries Brevo, Mailchimp 0/5 queries Omnisend appeared in 12 of 15 total queries — stronger entity presence than I expected. But mentions shifted dramatically by context. In ecommerce discussions, Klaviyo dominated as the top tool. In general email marketing, Mailchimp took over as the main reference point. The mention order revealed something important. Klaviyo appeared first in 5 of 5 ecommerce queries, with more positive language around their positioning. Omnisend routinely ranked second or third. This suggests they’re part of the discussion but not at the forefront. Here’s what’s interesting: Klaviyo completely disappeared from deliverability-focused queries while Omnisend maintained some presence. This shows entity relationships are radically contextual. Being the leader in ecommerce email doesn’t mean presence in deliverability conversations. 4. Optimize For Entities in Your Content Entity recognition works best when it has context-rich passages. This helps AI systems extract and understand information more easily. Take generic descriptions like “Our automation features help ecommerce businesses increase revenue through targeted campaigns.” An AI system may struggle to identify which product you mean, its automation features, or how it compares to others. Compare that to: “Omnisend’s SMS automation integrates with Shopify’s abandoned cart data to trigger personalized recovery messages within 2 hours of cart abandonment, without requiring manual workflow setup.” This version establishes multiple entity relationships (Omnisend → SMS automation → Shopify integration → abandoned cart recovery) within a single extractable passage. LLMs prefer to use their training data for answers. But when they pull info from the web, strong entity connections help a lot. You’re reducing friction for both bots and human readers. As a test, run key passages from your most important pages through Google’s Natural Language API to see what entities get recognized. This can also be video scripts. Content with strong entity density tends to get cited more often than content requiring additional context. 5. Build Strategic Co-Citations Entity authority builds through consistent mention alongside relevant entities in trusted sources. This moves the focus from link building to building relationships where natural comparisons happen. For Omnisend, this means being present in authentic discussions. It’s about genuine comparisons, not forced mentions, that strengthen specific relationships. A Reddit thread comparing “Klaviyo vs Omnisend for Shopify stores” carries a different entity weight than appearing in generic “email marketing tools” content. The specific context (Shopify integration) strengthens both brands’ association with ecommerce email marketing. The most valuable co-citations happen in: Reddit discussions comparing tools for specific use cases YouTube reviews demonstrating multiple platforms Industry roundups grouping tools by specialization Podcast discussions of marketing technology stacks This Reddit thread shows strategic co-citation in action. The original post creates dense entity relationships (Klaviyo → Omnisend → pricing → Shopify store). While the comment adds even more context (pricing concerns → business scaling → “pretty good” user experience). The discussion goes way beyond optimized content. It’s genuine decision-making that strengthens both brands’ entity associations with ecommerce email marketing. This approach emphasizes genuine participation. Your category is discussed and evaluated by actual users who make real decisions. This is better than having artificial mentions in content made mainly for search engines. Moving Forward with Entity SEO If you’ve built a strong brand across various channels, you’ve laid the foundation. Quality SEO is still crucial. Genuine mentions in industry talks, real customer chats, and multi-channel distribution matter too. Begin with your key product line. Organize it well, track its appearances in AI responses, and then expand to other entities. For more on succeeding in AI-powered search, check out our complete AI search strategy guide. The post Entity SEO in the Age of AI Search appeared first on Backlinko. View the full article

AI answers are taking over search. More people are turning to Google AI Overviews, ChatGPT, and Perplexity for recommendations. And if your brand isn’t showing up in those AI answers? You’re missing out on a huge (and growing) slice of your market. That’s why Semrush built the AI SEO Toolkit. It’s a major unlock for marketers trying to understand how AI is impacting their business. Today, I’m going to show you how to use it — step by step — with a real example. TL;DR: Measure Your AI Search Visibility Here’s what you need to know about Semrush’s AI SEO Toolkit: What it does: Tracks how your brand appears across ChatGPT, Google AI Overviews, Google AI Mode, and Perplexity — showing which prompts include you and where you’re missing Provides prompt tracking, content audits, and competitor comparisons What it costs: $99/month per domain (no trial) Step 0: Start With a Brand Before we analyze anything, let’s pick a brand to make this walkthrough concrete. I went to Exploding Topics, browsed the ecommerce category, and picked Petlibro — a trending startup that sells smart pet feeders and water fountains. I have zero affiliation with Petlibro. This isn’t sponsored. I just wanted a brand that’s growing fast and has enough search demand to make this example interesting. Step 1: Get Your Search Baseline Before we look at AI, we want to know how Petlibro is doing in traditional search. It’s super valuable context that will help us understand how they’re performing in LLMs. To understand their current search baseline, head to Semrush’s Domain Overview. Enter the brand’s domain name and look at the last 18 months. Looking at petlibro.com, they’ve been growing a TON. They get most of their traffic from the U.S., rank for more than 25,000 keywords, and have a domain Authority Score of 43 with backlinks from 2.8K referring domains. And they rank well in traditional SERPs for a bunch of highly relevant category and product keywords. So they’re a real brand that’s already doing a good job with SEO. And good search engine optimization often correlates with good AI optimization. If your brand has so far neglected SEO, now is the ideal time to tackle that with a solid AI SEO strategy (which this audit will help you form). Step 2: Check Your AI Visibility Now for the fun part. Back in the Semrush dashboard, look for AI SEO in the sidebar. Enter petlibro.com, and a few minutes later, your Brand Performance dashboard will be ready for review. On the right side, you can see the Share of Voice versus Sentiment Score. The most interesting thing I noticed right away is that Petlibro has relatively low Share of Voice (6%) in regular ChatGPT, without Search. That’s because ChatGPT 5 without search enabled has a training data cutoff of September 30, 2024. And as we saw in traditional search, Petlibro has been growing a LOT in the last year. Fortunately, they’re performing much better in SearchGPT, Google AI Mode, and Perplexity. All three of which use live search to generate their answers. For example, Petlibro’s Share of Voice in Google AI Mode is 27.8%: Pro tip: Keep this in mind when analyzing your own brand too. These tools might not have your newest content in their training data. This can affect your apparent visibility, so be sure to check your visibility when search is enabled (as search-powered experiences are becoming more common). This tab gives you a broad overview of your brand’s visibility. The next step will help you get more granular. Step 3. Gauge Visibility at the Prompt Level You can get prompt-level details by heading to the Visibility Overview tab. Note: Things are evolving fast in the AI SEO space. This tool is brand new at the time of writing, so there isn’t much in the way of historical data right now. But tracking your visibility here over time will help you understand how well optimized your site is for an increasingly AI-based search landscape. Scroll down and you’ll be able to quickly understand: Your top-performing topics Opportunities to improve your brand’s visibility Popular sources for prompts relevant to your industry Where your competitors are being cited that you’re not Where you are being cited as a source Click on any of the topics (or select Prompts) to see exact prompts and the AI response that you appear as part of. To get more data on the prompts your rivals are appearing for that you’re not, head to the Narrative Drivers tab. First, you’ll see your brand’s Share of Voice by platform. This gives you an overview of where your rivals are winning on each AI platform. But we want to scroll down to Share of Voice and switch to the Average Position view. You can then toggle each competitor individually to get a better idea of how you perform against key rivals over time. This view essentially gives you a snapshot of your brand’s visibility for key prompts. To understand which prompts you are and are not appearing for compared to your rivals, you want to scroll down to the Breakdown by Question section. You’ll see your position, which is where you show up in the answer snippet compared to your competitors. You can see which ones your rivals appear for that you don’t by using the filters: For example, Petlibro isn’t appearing for a few prompts that multiple competitors are mentioned in: Identify the most relevant queries you want to start appearing for, and do this for each AI tool (using the toggle at the top left). Note these down somewhere, as these will help frame your AI optimization strategy. Think of this part like the keyword research stage in a traditional SEO campaign. Step 4. Review Your Brand’s Trust Factors Next, you want to understand where your brand is doing a good job of appearing trustworthy to both your users and the LLMs themselves. To do this, head back to the Brand Performance tab and scroll down to Key Business Drivers. This essentially shows where your brand is strong compared to your competitors in various areas that help convey trust to users. It might look overwhelming at first. But basically: The numbers illustrate how often key business drivers (i.e., trust factors) appear in answers where your brand is also mentioned. The bigger the number, the better. (Look for the trophy icon to see where you’re currently ahead of your competitors.) For example: Searchers may value smart home integration when selecting a smart pet feeder. When AI tools mention PetSafe, they also sometimes mention the fact it has these features. This makes the brand more likely to appear in AI search responses when a user is looking for smart pet feeders with features like smart home integrations. If Petlibro offers this, the brand needs to do a better job of conveying that in their content, or they’re going to struggle to appear in AI responses for relevant prompts. Meanwhile, PetSafe is being mentioned for this kind of user prompt: Go through this tab and identify trust factors you want to appear for. If you spot areas competitors are strong but you’re not being picked up, make sure you: Include trust factors and unique selling points on your website homepage Add mentions of relevant features to product pages Write helpful FAQ questions on product pages and blog posts that cater to these trust factors Step 5. Audit Brand Sentiment in AI Tools The next step involves diving deeper into how AI tools (and by proxy your users) perceive your brand. To do this, we’ll head to the Perception report and scroll to the Key Sentiment Drivers section. This will show you Brand Strength Factors and Areas for Improvement. This is a great snapshot to see where you’re already doing well. And where you might need to focus new efforts on improving your brand’s perception in AI responses. Brand strength factors are essentially areas where the AI tools talk positively about your brand. In Petlibro’s case, these are factors like app connectivity, mechanical jams, and customer support. Pro tip: Look for anything that’s not accurate here. You don’t want AI tools to be recommending your brand for things you don’t offer — this will just lead to disappointed customers. The areas for improvement are areas where you might want to: Create optimized content to make it clear to customers what you offer Optimize your existing product pages to better reflect their strengths Improve your products or services to better meet your customers’ needs That final point is worth emphasizing. Semrush’s AI SEO tools don’t just give you content ideas. You can use the insights you gain here and the prompts real users are inputting into AI tools to understand where you can improve and expand your products/services. The future of marketing is truly collaborative across departments. And these kinds of insights can help align both your SEO/content teams and your product and marketing divisions. This can lead to a better user experience on your site, a better product for your customers, and increased business growth. Pro tip: At the bottom of most of these tabs, you’ll also find “AI Strategic Insights.” These are AI-powered suggestions you can use immediately to boost your AI visibility. Step 6. Identify More Content Ideas Step 6 is to find more ideas for creating new content and optimizing your existing pages. First, head to the Questions tab and scroll down to the Query Topics section. Answer these questions with new content or in your existing content. For example, Petlibro could create a blog post titled “How to Stop Your Cat Shaking Food Out of Its Feeder.” They could also update their product pages to highlight that their feeders support different portion sizes for morning and evening meals, and add an FAQ section answering common branded questions. To understand what content you might want to create (and which prompts are actually worth optimizing for), enter the relevant ones into tools like ChatGPT. (Make sure you enable web search.) The example below returns a lot of scientific papers, so it would likely be a tough one for Petlibro to appear for. But there is a Reddit thread in there too. Which means a Reddit marketing strategy could be worth exploring to boost visibility for these kinds of prompts. This next one is a more likely candidate, and we can see PetSafe (a competitor) gets cited as a source. (And Reddit appears again too.) There is also a product carousel with links further down — none of which are from Petlibro. So this would definitely be worth digging into to see why PetSafe (and the other products) are being recommended: Do the product pages do a better job of conveying trust signals? Are they more descriptive? Do they have FAQ sections that answer the prompt’s question? Bottom line: You need to look closer than simply the prompts themselves to understand why other brands are being recommended ahead of yours. But once again, if you scroll to the bottom, you’ll find AI-powered insights that can give you a head start. Turn Your AI SEO Audit Insights Into Action An AI SEO audit is a vital first step to make your brand AI ready. And Semrush’s AI SEO Toolkit gives you everything you need to get started. But the audit is just the first step. Use these resources to turn what you learn from the tool into action for your brand: AI Search Strategy: The Seen & Trusted Brand Framework 5 LLM Visibility Tools to Track Your Brand in AI Search (2025) LLM Seeding: A New Strategy to Get Mentioned and Cited by LLMs The post Semrush AI SEO: How to Audit Your AI Search Visibility appeared first on Backlinko. View the full article

Want more housing market stories from Lance Lambert’s ResiClub in your inbox? Subscribe to the ResiClub newsletter. A recent Zillow analysis suggests it would take a drop of more than one percentage point—to 4.43%—for the median-income U.S. homebuyer to comfortably afford the median-priced U.S. home. And that assumes a 20% down payment, which many first-time buyers are unable to make. Even more striking, in several high-cost coastal metros, not even a 0% mortgage rate would make the median-priced local home affordable for a household earning the local median income. This includes New York, Los Angeles, Miami, San Francisco, San Diego, and San Jose, where taxes, insurance, and maintenance on a median-priced home alone can often consume more than 10% of a median household’s income. On the flip side, Zillow finds that mortgage rates are already low enough for median-income buyers in many Midwestern markets to afford the median-priced home in those areas. Keep in mind, this is back-of-the-envelope math. The mortgage rate scenarios above assume all else is equal—and that lower rates don’t impact home prices. Are we likely to see an average 30-year fixed mortgage rate of 4.43% anytime soon? Zillow economists say that scenario is “unrealistic”—at least in the short term. “Holding incomes, [U.S.] home prices and all other housing-related costs equal, mortgage rates would need to drop to 4.43% in order for a typical home to be affordable to a buyer making the median income, assuming they put 20% down. That kind of a rate decline is currently unrealistic,” wrote Zillow economic analyst Anushna Prakash. Prakash added that: “If buyers are waiting for big drops in mortgage rates or [U.S. home] prices to help affordability, they’re in for a rude awakening. Just like falling rates, that kind of correction in house prices won’t happen without a serious slowdown in economic growth and income growth, and a rise in the unemployment rate.” View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. Marshall speakers are known for their iconic retro looks and powerful audio, so if you’re in the market for a desktop speaker that isn’t an eyesore and still delivers solid sound, the Marshall Emberton II portable Bluetooth speaker is currently around $95, 47% off the usual price. Marshall Emberton II Portable Bluetooth Speaker $94.99 at Amazon $179.99 Save $85.00 Get Deal Get Deal $94.99 at Amazon $179.99 Save $85.00 Mimicking the classic Marshall amp aesthetic, this vintage-inspired speaker provides rich bass and bright highs, according to this PCMag review, which notes that while the speaker can get impressively loud, it comes at the expense of bass depth and a warped sound signature. The Push mode can help balance out those EQ changes, but you still won’t get truly deep low-end. It’s ideal for indoor use, but it may not be loud enough to provide immersive sound in a backyard or on adventures. The speaker also lacks strong digital signal processing at high volumes, and doesn’t include a built-in mic or speakerphone functionality. Compared to its predecessor, the Emberton II is longer lasting and more durable. It has a dust-tight build and an IP67 rating, which means it can be submerged in up to a meter of water for 30 minutes. It can go for 30 hours without recharging, but that number will vary based on how loud you play it. Charging the speaker for 20 minutes provides four hours of playtime, but a full charge requires three hours. The companion Marshall Bluetooth app is only so-so; there are just three preset modes to adjust EQ. If you can deal with occasionally aggressive digital signal processing and iffy low-end, the Marshall Emberton II is a stylish, well-built speaker that provides a decent audio experience for most songs. At $95, it’s a more affordable (and more aesthetic) alternative to similar speakers from the likes of JBL. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods Pro 2 Noise Cancelling Wireless Earbuds — $197.00 (List Price $249.00) Samsung Galaxy S25 Edge 256GB Unlocked AI Phone (Titanium JetBlack) — $819.99 (List Price $1,099.99) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $319.00 (List Price $349.00) Blink Mini 2 1080p Indoor Security Camera (2-Pack, White) — $34.99 (List Price $69.99) Ring Battery Doorbell Plus — $149.99 (List Price $149.99) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $34.99 (List Price $69.99) Ring Indoor Cam (2nd Gen, 2-pack, White) — $79.99 (List Price $99.98) Amazon Fire TV Stick 4K (2nd Gen, 2023) — $29.99 (List Price $49.99) Shark AV2501S AI Ultra Robot Vacuum with HEPA Self-Empty Base — $359.89 (List Price $549.99) Amazon Fire HD 10 (2023) — (List Price $139.99) Deals are selected by our commerce team View the full article

A reader writes: I am part of a small team in a global corporation. My team works closely with other teams in the department, and we often have weekly or biweekly catch-ups to update each other on projects. My colleagues are mostly nice and pleasant to work with. There’s only one problem: everyone is obsessed with Taylor Swift. And I don’t mean it in a “owns a few of her albums and liked them” sort of way. It’s something more akin to religious fervor. They log in from rooms plastered with Taylor Swift posters and talk about her in almost every meeting. They sneak references in marketing content. The passwords we use for our shared software accounts are all Taylor Swift-based. it’s been going on for months. I seem to be one of the very few people who doesn’t have strong opinions about Taylor Swift, one way or the other: I don’t love her. I don’t hate her. I occasionally bob my head to one of her songs when they come up on the radio. But this is somewhat affecting the way we work. As everyone knows (whether they like it or not), recently Swift’s new album came out. We had three separate meetings in which the icebreaker was related to this release, such as “which was your favorite song from The Life of a Showgirl?” I found myself scrambling to listen to a few songs just so I could have an answer ready and wouldn’t have to stand there in awkward silence. Our company is going through a tough time lately, and I’m genuinely happy for these people to have reasons to be excited, so I feel bad about asking them to tone the Taylor Swift talk down a little. But at the same time, I could do with getting 5-10 minutes of my time back by keeping it to private chats, and I am not thrilled about giving myself homework in case of pop quizzes. How can I opt out from the cult without being a buzzkill? You need to come out and say you don’t follow Taylor Swift! By doing things like listening to songs from her new album just so you’ll have an answer ready for Swift-based icebreakers, you’re actually making it worse — because you’re reinforcing that this is an icebreaker everyone can participate in, when that’s the opposite of what you want. It would be far more effective toward your long-term goal if you instead said, “I don’t really listen to Taylor Swift, so I can’t contribute.” Let that truth make the point that that something they’re assuming is universal is in fact not universal. And if they keep making icebreakers Swift-themed after that, you’d have plenty of standing to say, “Could we do icebreakers everyone can participate in?” and maybe, “This is like having every icebreaker be soccer-themed or something else that not everyone follows.” A similar principle applies to the constant Taylor Swift chat. People definitely get to chat about what they want with coworkers (within reasonable boundaries), but at a certain point it’s also fair game for you to say, “Y’all, this is a lot when not all of us are fans. Can we talk about anything else?” And if you get people who respond to that by trying to turn you into a fan, you can say, “Truly, I’m good. She’s just not my cup of tea, and this is a very Swift-talk heavy office!” If that doesn’t work, move to: “I would love not to be evangelized at, thank you for understanding.” The post my office is obsessed with Taylor Swift appeared first on Ask a Manager. View the full article

Patrick James borrowed billions — even after presiding over a string of failed businessesView the full article

Target market for Erebor will be businesses that are part of America’s ‘innovation economy’View the full article

IBM has just unveiled its Spyre Accelerator, a new tool that promises to transform how small and medium-sized enterprises harness the power of artificial intelligence (AI). Set to be generally available on IBM z17 by October 28, 2025, this groundbreaking technology aims to streamline AI integration within established and secure environments, accommodating various business needs. The Spyre Accelerator empowers businesses with the ability to leverage large language models (LLMs) through internal operations. This opens the door to using natural language interfaces like the watsonx Assistant for Z. Small business owners can look to incorporate generative AI into many aspects of their operations—from enhancing customer interactions to refining data management practices. One of the key benefits of the Spyre Accelerator is its capacity to merge generative and predictive AI techniques, providing a comprehensive solution for various business applications. For instance, enterprises can develop more accurate AI strategies for generating content or interpreting customer data. This can lead to productive outreach initiatives, as well as informed risk assessments and cross-offer opportunities—all in real time. A case study from a major European bank underscores the importance of maintaining production workloads in trusted environments. The bank’s infrastructure lead stated, “On-prem with Spyre Accelerator for IBM Z is important to us because this work will be related to production code. We don’t want production workloads leaving our hands, so it is our favorite option.” This highlights a vital practical application for small business owners: the assurance of keeping sensitive data secure while employing advanced AI technologies. Utilizing AI-driven tools facilitates rapid decision-making, which can be a game-changer for small businesses, especially during peak transaction days. By automatically predicting next actions and suggesting optimized outputs from new applications via recommended agents and APIs, the Spyre Accelerator aims to accelerate businesses’ time to value. A 2024 study by the Institute for Business Value and Oxford Economics found that 61% of executives believe generative AI is crucial for application modernization on mainframes. This statistic emphasizes the increasing recognition of AI’s role in not just innovation but also in maintaining the relevance of existing systems and processes. The Spyre Accelerator is built to deliver on-premises support for large language models, featuring 32 AI-optimized processing cores designed to run generative AI applications securely within the IBM Z framework. This significant upgrade enables businesses to scale their AI initiatives while maintaining data integrity. Small business owners may consider the infrastructure implications as they contemplate integrating the Spyre Accelerator. While the benefits are compelling, it is vital to assess whether their current systems can efficiently adapt to this new technology. Moreover, understanding the complete cost structure associated with implementing such advanced tools is crucial for long-term planning. IBM’s commitment to continuous improvement means that critical software products, such as the AI Toolkit for IBM Z and the Machine Learning for IBM z/OS, will be enhanced by Spyre Accelerators, ensuring businesses enjoy comprehensive on-prem deployment capabilities. This kind of ongoing upgrade could translate into a significant competitive edge. The Spyre Accelerator marks an essential evolution in how small businesses can approach AI. Through its focus on security and efficiency, it allows enterprises to scale their operations without compromising data integrity. The intersection of generative AI and established infrastructure could provide new opportunities for growth and innovation in the small business landscape. For more information on IBM’s new features and offerings, check out the original press release. Image via IBM This article, "IBM’s Spyre Accelerator Brings Generative AI to z17 for Enhanced Business Efficiency" was first published on Small Business Trends View the full article

IBM has just unveiled its Spyre Accelerator, a new tool that promises to transform how small and medium-sized enterprises harness the power of artificial intelligence (AI). Set to be generally available on IBM z17 by October 28, 2025, this groundbreaking technology aims to streamline AI integration within established and secure environments, accommodating various business needs. The Spyre Accelerator empowers businesses with the ability to leverage large language models (LLMs) through internal operations. This opens the door to using natural language interfaces like the watsonx Assistant for Z. Small business owners can look to incorporate generative AI into many aspects of their operations—from enhancing customer interactions to refining data management practices. One of the key benefits of the Spyre Accelerator is its capacity to merge generative and predictive AI techniques, providing a comprehensive solution for various business applications. For instance, enterprises can develop more accurate AI strategies for generating content or interpreting customer data. This can lead to productive outreach initiatives, as well as informed risk assessments and cross-offer opportunities—all in real time. A case study from a major European bank underscores the importance of maintaining production workloads in trusted environments. The bank’s infrastructure lead stated, “On-prem with Spyre Accelerator for IBM Z is important to us because this work will be related to production code. We don’t want production workloads leaving our hands, so it is our favorite option.” This highlights a vital practical application for small business owners: the assurance of keeping sensitive data secure while employing advanced AI technologies. Utilizing AI-driven tools facilitates rapid decision-making, which can be a game-changer for small businesses, especially during peak transaction days. By automatically predicting next actions and suggesting optimized outputs from new applications via recommended agents and APIs, the Spyre Accelerator aims to accelerate businesses’ time to value. A 2024 study by the Institute for Business Value and Oxford Economics found that 61% of executives believe generative AI is crucial for application modernization on mainframes. This statistic emphasizes the increasing recognition of AI’s role in not just innovation but also in maintaining the relevance of existing systems and processes. The Spyre Accelerator is built to deliver on-premises support for large language models, featuring 32 AI-optimized processing cores designed to run generative AI applications securely within the IBM Z framework. This significant upgrade enables businesses to scale their AI initiatives while maintaining data integrity. Small business owners may consider the infrastructure implications as they contemplate integrating the Spyre Accelerator. While the benefits are compelling, it is vital to assess whether their current systems can efficiently adapt to this new technology. Moreover, understanding the complete cost structure associated with implementing such advanced tools is crucial for long-term planning. IBM’s commitment to continuous improvement means that critical software products, such as the AI Toolkit for IBM Z and the Machine Learning for IBM z/OS, will be enhanced by Spyre Accelerators, ensuring businesses enjoy comprehensive on-prem deployment capabilities. This kind of ongoing upgrade could translate into a significant competitive edge. The Spyre Accelerator marks an essential evolution in how small businesses can approach AI. Through its focus on security and efficiency, it allows enterprises to scale their operations without compromising data integrity. The intersection of generative AI and established infrastructure could provide new opportunities for growth and innovation in the small business landscape. For more information on IBM’s new features and offerings, check out the original press release. Image via IBM This article, "IBM’s Spyre Accelerator Brings Generative AI to z17 for Enhanced Business Efficiency" was first published on Small Business Trends View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. Did you know you can customize Google to filter out garbage? Take these steps for better search results, including adding Lifehacker as a preferred source for tech news. If you’ve been looking to upgrade your portable speaker game before the next beach day or house party, the JBL Flip 6 deal on Woot might catch your eye. It’s currently down to $79.95, a solid $50 off its usual price of $129.95. The sale runs for ten days or until supplies last, with free shipping available to Prime members (others pay $6). That said, Woot does not ship to Alaska, Hawaii, or PO box addresses, and the warranty on this is a modest 90 days. Still, for what’s easily its lowest price ever (according to price-tracking tools), it’s worth a look. It weighs just over a pound and measures about seven inches long, with the same cylindrical design that’s made the Flip series so recognizable. A woven grille wraps around its body, flanked by passive radiators on both ends that thump out low-end sound with surprising confidence. Inside, you’re getting a 20-watt woofer and a 10-watt tweeter, which together deliver a frequency range of 63Hz to 20kHz. The result is a deep, balanced sound with a punchy midrange and enough bass to feel satisfying without muddying vocals, notes this PCMag review. It connects via Bluetooth 5.1 and supports AAC and SBC codecs, though there’s no AptX, aux input, or speakerphone feature—something to keep in mind if you prefer wired flexibility or take calls through your speaker. For outdoor use, though, the Flip 6 hits its stride. With its IP67 rating, it’s fully dust-proof and waterproof (drop it in a pool or rinse off the sand, and it’ll keep playing). Battery life runs around 12 hours, depending on your volume levels, and the USB-C charging port supports modern charging speeds. It’s also compatible with the JBL Portable app, where you can tweak the EQ if you like tailoring your sound, manage PartyBoost (to link other JBL speakers), and update firmware. It’s not a mini subwoofer, but for its size and price, the Flip 6 punches above its weight. Our Best Editor-Vetted Tech Deals Right Now Apple AirPods Pro 2 Noise Cancelling Wireless Earbuds — $197.00 (List Price $249.00) Samsung Galaxy S25 Edge 256GB Unlocked AI Phone (Titanium JetBlack) — $819.99 (List Price $1,099.99) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $319.00 (List Price $349.00) Blink Mini 2 1080p Indoor Security Camera (2-Pack, White) — $34.99 (List Price $69.99) Ring Battery Doorbell Plus — $149.99 (List Price $149.99) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $34.99 (List Price $69.99) Ring Indoor Cam (2nd Gen, 2-pack, White) — $79.99 (List Price $99.98) Amazon Fire TV Stick 4K (2nd Gen, 2023) — $29.99 (List Price $49.99) Shark AV2501S AI Ultra Robot Vacuum with HEPA Self-Empty Base — $359.89 (List Price $549.99) Amazon Fire HD 10 (2023) — (List Price $139.99) Deals are selected by our commerce team View the full article

Grunt work is no longer the rite of passage. It's Not Just the Numbers With Penny Breslin and Damien Greathead For CPA Trendlines Go PRO for members-only access to more Penny Breslin. View the full article

Grunt work is no longer the rite of passage. It's Not Just the Numbers With Penny Breslin and Damien Greathead For CPA Trendlines Go PRO for members-only access to more Penny Breslin. View the full article

If you’re running Performance Max, or planning to launch a new campaign, I want to clear up one of the most misunderstood parts of Google Ads: audience signals and search themes. Understanding how to use (and not misuse) signals can strongly impact your PMax success. Why Performance Max is different than other Google Ads campaign types If you stop reading here and take nothing else away from this article, remember this: You do not get to pick your audience or keyword targeting in PMax. This is where a lot of advertisers get tripped up. Unlike traditional Search campaigns where you build a keyword list, or Demand Gen where you choose specific demographics or interest-based audiences, or Display/Video where you can pick exact content placements – PMax is purely a goal-based campaign. Its primary directive is to achieve your conversion goal. That means your conversion tracking and your bid strategy are what actually determine who sees your ads. “Under the hood” of Performance Max, optimized targeting and dynamic search technology decide who will see your ads, based on how likely Google thinks they are to help you achieve your goals. You can provide the AI with a starting set of directions or “suggestions” via audience signals and search themes. If the AI likes your suggestions, it will follow them. And if it doesn’t, it will ignore them. Audience signals vs. audience targeting What really happens when you add audience signals to an asset group in your PMax campaign? You’re giving the AI a hint about who your ideal customer might be. Or to use Google’s words, you’re combining your expertise with Google’s AI. Within the Google Ads interface, these audience signals look exactly like audience targeting. Your Performance Max audience signals can include: Your Data Segments: Customer lists (Customer Match), YouTube viewers, website visitors, etc. Google Segments: In-market, affinity, detailed demographic, or life events. Custom Segments: Based on interests, websites or apps. The key thing to remember is that these are just signals. The AI takes your suggestions, but it’s not restricted to them. For example, let’s say you give your PMax campaign the affinity segment “luxury shoppers” as an audience signal, because you sell high-end products. If the AI, over time, sees that the affinity segment “value shoppers” actually click through your ads and convert at a better rate, it prioritize serving ads to those value shoppers rather than luxury shoppers. The AI will go where the conversions are, regardless of your initial signal. This is why conversion tracking is paramount. Contrast that with a Demand Gen campaign. If you add the affinity segment “luxury shoppers” to Demand Gen, and optimized targeting is turned off, you will only show ads to users who match the luxury shoppers segment – even if it doesn’t convert well. If you use the Maximize Conversions bid strategy, Demand Gen will continue to spend your budget anyway. If you use Target CPA or Target ROAS, Demand Gen may stop spending if it can’t get conversions at an appropriate ROI out of your selected audience. Search themes vs. keyword targeting The same principle applies to search themes in Performance Max. If you’re familiar with keyword-based Google Search campaigns, you might assume search themes are just a new name for keywords – but they’re absolutely not the same thing. In a Search campaign, a keyword sets rules around which queries can trigger your ads. Those rules may be broader than you want them to be, but that’s a topic for a different day! The point is, you can only serve ads on queries that match your keywords. In PMax, a search theme is an optional suggestion you provide to the AI about the kinds of queries you think your ideal customer is using. If queries that match those search themes convert well and meet your goals, then you’ll continue to serve ads there. If they don’t, you won’t. Why would you use search themes? Some use cases might be: To give your PMax campaign a “head start” on the types of queries you want If you’re launching a new product and Google’s AI hasn’t had enough time to crawl your assets and landing pages to figure out the right search queries yet If you want to let Google know you’re interested in showing up on competitor-related searches. However, if you give the AI 50 search themes (the current maximum per asset group) that are not relevant to your website or that simply don’t lead to conversions, the PMax campaign is not going to spend its budget chasing those themes. It will prioritize the search queries that the data shows are most likely to convert, even if they aren’t included in your search themes. Again, this is why conversion tracking is paramount. How to actually control your Performance Max campaign targeting So, if signals aren’t the primary control for Performance Max targeting, what is? If you want to influence where your ads show up, you need to focus your efforts on the core elements of the campaign. Those are: Conversion Tracking: This is like the compass for your AI-powered self-driving car. It must be set up accurately and be measuring the actions that are truly valuable for your business. Bid Strategy: This tells PMax whether to focus on volume (Maximize Conversions, Maximize Conversion Value) or efficiency (Target CPA, Target ROAS). Because PMax only uses Smart Bidding, your conversion tracking is the key foundation required for your bid strategy to be effective. Assets (Creative): Your headlines, descriptions, images, and videos are all that the end user sees, so this determines whether or not they’ll engage with your ads, visit your landing page, and convert or not convert. The messages you convey via your assets “drive” your targeting much more than your optional signals. Should you use audience signals and search themes? By all means, use audience signals and search themes in your Performance Max campaigns. They can be helpful starting points, especially for new campaigns or when you have high-quality first-party data (like a Customer Match list). Just remember that your PMax campaign could still serve ads to absolutely no one who matches any of the signals you provided, if the AI determines those people don’t convert as well as other segments. Don’t mistake signals for targeting! One more PMax mistake to avoid I often see this mistake when I audit Google Ads accounts: running a Performance Max campaign with multiple asset groups that have the exact same creative assets but use different audience signals/search themes. I will repeat one more time: signals are not targeting! By running the same assets multiple times over, all you’re doing is fragmenting the AI’s learning and wasting money on duplication. The entire reason you create a different asset group is because you have different assets. If you’d like to give those groups different signals, go for it. If you’d like to give them all the same signals, also go for it. The distinction between asset groups should be the creative and/or product mix, not just the signals. This article is part of our ongoing bi-weekly Search Engine Land series, Everything you need to know about Google Ads in less than 3 minutes. Every other Wednesday, Jyll highlights a different Google Ads feature, and what you need to know to get the best results from it – all in a quick 3-minute read. View the full article

Here is a recap of what happened in the search forums today...View the full article